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LICENSE.txt

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-version https://git-lfs.github.com/spec/v1
-oid sha256:149d807167937014a4633d3a72ce59e201b01087b08c901257bd17c416481bc5
-size 1071
+MIT License
+
+Copyright (c) Namitha Padmanabhan
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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-version https://git-lfs.github.com/spec/v1
-oid sha256:881c0ec81d89da3e6b8b32c9efd8a46e14a71ee5218de4b7c4908f151c34cb24
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+---
+license: mit
+tags:
+  - video-compression
+  - implicit-neural-representations
+  - hypernetwork
+  - pytorch
+---
+
+# TeCoNeRV Model Checkpoints
+
+TeCoNeRV uses hypernetworks to predict implicit neural representation (INR) weights for video compression. A patch-tubelet decomposition enables hypernetworks to scale to high-resolution video prediction. The temporal coherence objective reduces redundancy across consecutive clips, enabling compact residual encoding of per-clip parameters.
+
+This repository contains hypernetwork training checkpoints for the three model families described in the paper.
+
+## Model families
+
+`nervenc` — Baseline NeRVEnc hypernetwork. Predicts full-resolution clip reconstructions directly.
+
+`patch_tubelet` — Proposed patch-tubelet hypernetwork. Predicts parameters for spatial tubelets; full frames are reconstructed by tiling. Supports resolution-independent inference.
+
+`teconerv` — Proposed method. Initialized from a `patch_tubelet` checkpoint and finetuned with a temporal coherence objective.
+
+## Getting started
+
+See the [GitHub repository](https://github.com/namithap10/TeCoNeRV) for full documentation on setup, training, and evaluation. Checkpoint download instructions are in `docs/models.md`.
+
+```bash
+git lfs install
+git clone https://huggingface.co/namithap/teconerv-models
+```
+
+## Citation
+
+```bibtex
+@article{padmanabhan2026teconerv,
+  title={TeCoNeRV: Leveraging Temporal Coherence for Compressible Neural Representations for Videos},
+  author={Padmanabhan, Namitha and Gwilliam, Matthew and Shrivastava, Abhinav},
+  journal={arXiv preprint arXiv:2602.16711},
+  year={2026}
+}
+```